基于烟花算法的PHEV能量管理策略参数优化

为改善插电式混合动力汽车(PHEV)的燃油经济性,提出一种基于规则的能量管理策略。结合智能网联汽车技术,利用烟花算法(FWA)结合系统约束条件,对能量管理策略参数进行优化,以求使车辆在变化的路况下能耗最低。为减轻沉重运算负荷,设计了一种事件触发机制来控制优化操作的启停。当车辆油耗超过预设上限则开始优化,一旦油耗满足预设下限则优化结束。在中国典型城市工况下,验证了该策略的有效性及优化性能。结果显示:较优化前的能量管理策略,该方案可使PHEV燃料消耗降低10%。从而,使燃油经济性明显提升。

Parameter optimization of energy management strategy for PHEVs based on firework algorithm

A rule-based energy management strategy(EMS)was designed to improve the fuel economy of a plug-in hybrid electric vehicle(PHEV).A firework algorithm(FWA)was adopted combined with intelligent network vehicle technologies to optimize the EMS parameters considering powertrain constraints,to minimum vehicle energy consumption under changing driving cycles.An event-triggered mechanism was used to determine the start and the stop of this operation to avoid overloaded computing burden.The optimization would be started just when PHEV fuel consumption exceeds the preset upper limit,and would be ended once the fuel consumption drops to the preset lower limit.The EMS performances were verified under China typical urban driving cycles.The results show that the strategy reduces10%of the PHEV fuel consumption over that by using the unoptimized rule-based strategy.Therefore,the strategy improves obviously vehicle fuel economy.